Special Research Initiatives - Grant ID: SR0566892
Funder
Australian Research Council
Funding Amount
$220,000.00
Summary
The EarthByte software and database system. Earth processes over geological timescales cannot be understood outside of a plate tectonic context. However, no standard tool exists to explore the causes and effects of lithosphere-mantle interaction in accordance with past plate configurations. Our aim is to develop a Palaeo-Geographic Information System called EarthByte that will connect the open source and architecture-independent GPlates and GMT software, and implement XML-based service interfac ....The EarthByte software and database system. Earth processes over geological timescales cannot be understood outside of a plate tectonic context. However, no standard tool exists to explore the causes and effects of lithosphere-mantle interaction in accordance with past plate configurations. Our aim is to develop a Palaeo-Geographic Information System called EarthByte that will connect the open source and architecture-independent GPlates and GMT software, and implement XML-based service interfaces and databases. EarthByte will create the foundation for an e-geoscience framework for grid-based data access and Earth process modelling by linking geological and geophysical observations to palaeogeographic models for constraining mantle convection and lithospheric deformation.Read moreRead less
Algorithms for Future-Proof Networks. This project will design algorithms to construct, augment and route on geometric graphs in the presence of obstacles. Such graphs have many real-world applications, including transport networks. This project aims to give solutions with hard guarantees on the timeliness of the delivery of the people, goods, or information being transported in these networks. Expected outcomes of this project include efficient and innovative algorithms for realistic geometric ....Algorithms for Future-Proof Networks. This project will design algorithms to construct, augment and route on geometric graphs in the presence of obstacles. Such graphs have many real-world applications, including transport networks. This project aims to give solutions with hard guarantees on the timeliness of the delivery of the people, goods, or information being transported in these networks. Expected outcomes of this project include efficient and innovative algorithms for realistic geometric graphs, which both advances the knowledge in this field of computer science and make our existing networks more reliable. This should provide significant benefits in the maintenance and utilisation of the communication and transport networks we use every day.Read moreRead less
A Data-Centric Mobile Edge Platform for Resilient Logistics & Supply Chain. This project aims to develop a secure mobile edge computing platform for resilient logistic and supply chain management. It consists of easy-used functions that help businesses realise low latency, high reliability, low cost, and high security in their logistics and supply chain system. To cope with the vast generated application data, we invent new data replication, placement, and deduplication techniques to optimise th ....A Data-Centric Mobile Edge Platform for Resilient Logistics & Supply Chain. This project aims to develop a secure mobile edge computing platform for resilient logistic and supply chain management. It consists of easy-used functions that help businesses realise low latency, high reliability, low cost, and high security in their logistics and supply chain system. To cope with the vast generated application data, we invent new data replication, placement, and deduplication techniques to optimise the mobile edge computing platform from the computation, storage, and network aspects. The invented mobile edge computing platform will enable more intelligent business applications for various industries, e.g., IT, manufacturing, and media, to appear, thus benefiting both the economy of Australia.Read moreRead less
Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research ....Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research will include new data privacy models, new privacy-preserving data mining algorithms, and a prototype of cloud data mining software. These will help businesses cut costs for data mining and privacy protection, and provide significant benefits toward helping Australia achieve its national cyber security strategy and potentially provide economic impact from commercialisation of new software technology for the industry partner.Read moreRead less
Knowledge Graph-driven Software Vulnerability Risk Discovery and Assessment. This project aims to alleviate cyberattacks which are increasingly being crafted to attack software vulnerabilities and weaknesses by utilising advanced knowledge graphs and deep learning techniques. This project expects to construct an innovative software vulnerability knowledge graph and develop advanced graph-based algorithms and models. Expected outcomes of this project include the enhanced capacity to defend agains ....Knowledge Graph-driven Software Vulnerability Risk Discovery and Assessment. This project aims to alleviate cyberattacks which are increasingly being crafted to attack software vulnerabilities and weaknesses by utilising advanced knowledge graphs and deep learning techniques. This project expects to construct an innovative software vulnerability knowledge graph and develop advanced graph-based algorithms and models. Expected outcomes of this project include the enhanced capacity to defend against cyberattacks for both organisations and individuals in Australia and beyond, theory development in graph theory, refined graph neural network models and improved graph transfer learning algorithms.Read moreRead less
Talking about place: tapping human knowledge to enrich national spatial data sets. Place descriptions are a common way for people to describe a location, but no current tools are smart enough to understand them. Emergency call centres are risking lives, users of navigation or web services are frustrated and addressing these problems costs billions of dollars per year. This project comes with a novel, interdisciplinary approach to automatically interpret human place descriptions and will develop ....Talking about place: tapping human knowledge to enrich national spatial data sets. Place descriptions are a common way for people to describe a location, but no current tools are smart enough to understand them. Emergency call centres are risking lives, users of navigation or web services are frustrated and addressing these problems costs billions of dollars per year. This project comes with a novel, interdisciplinary approach to automatically interpret human place descriptions and will develop novel methods to capture placenames with their meaning for smarter databases and automatic interpretation procedures. This acquired knowledge will be an important step forward for Australia's data custodians and users. Australia's location information industry will gain a significant advantage on a highly competitive global market.Read moreRead less
Onset Theory: Pushing the design envelope for textile composite structures. This study aims to exploit an innovative physics-based approach to predict the strength of textile composites. This is particularly important in areas such as aircraft design, where drastic weight savings are needed to allow designers to remain competitive in a low-carbon future. Improved theory and design tools will remove conservatism and account for a large part of these weight savings. The new approach is the first t ....Onset Theory: Pushing the design envelope for textile composite structures. This study aims to exploit an innovative physics-based approach to predict the strength of textile composites. This is particularly important in areas such as aircraft design, where drastic weight savings are needed to allow designers to remain competitive in a low-carbon future. Improved theory and design tools will remove conservatism and account for a large part of these weight savings. The new approach is the first to be consistent at all length scales — from atoms to aeroplanes — ensuring relevance for new and evolving composite material systems. A novel understanding of crack initiation in textile laminates is intended to reduce design and certification effort for new aircraft and help to design more efficient airframes at a lower cost.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while pres ....Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while preserving the data privacy. These tools should provide significant benefits to the privacy of cloud users, as well as financial and reputation benefits to the IT industry, by significantly reducing the likelihood of massive user data privacy breaches in the event of a cyber-hacking attack on the cloud server.Read moreRead less